MASS CUSTOMIZATION AND CO- CREATION ON SOCIAL …

Abstract: What customers are seeking now is

customization, products made to order. In their desire to

become customer driven, many companies have turned to

new programs and processes to meet every customer’s

request. One of the emerging paradigms today are ‘mass

customization' and 'co-creation'. Mass customization is a

production strategy focused on creation of products that

are uniquely customized to the customers. To produce

personalized products or services, and provide unique

value to their customers, companies increasingly involve

customers in product and service development – a

process of co-creation. Information about mass

customization and co-creation are present in industry

and science, but valuable data could also be found on

social networks. In this paper authors analysed the

visibility and presence of mass customization and co-

creation on social network Twitter, using data mining

technique. Twitter is a global social media platform and

it is nothing less than a goldmine when it comes to data

and information. Nearly all tweets are public and easily

extractable, which makes it easy to gather large amount

of data from twitter for analysis. Data mining is used in

order to extract data from Twitter, and analyzing it with

the intention of finding trends and patterns.

Key Words: Mass customization, Co-creation, Social

media, Social networks, Twitter, Data mining

1. INTRODUCTION

In today's turbulent era, it is very difficult to achieve

a competitive advantage on the market. Changes in

business are everyday, technology becomes more

advanced in a very short period of time, users have more

knowledge about products and services than they ever

had. Users are no longer passive receivers of information

and today they are becoming more and more active in the

process of creating products, starting from design to

creation of promotional messages In recent years, mass

media has changed and adopted a new phenomenon

called social media. The first part of this terminology,

social, refers to the need of people to connect and

communicate with other people and the second part

refers to the media that people use to connect with other.

Applying term social media means that people can use

all available technologies effectively, interact and

connect with other people, build relationships, trust, and

be there when people in these relationships are ready to

buy the product offered by some company. The rise of

interactive digital media has changed the model of

communication between companies and customers.

Companies have to change own business strategy

continously, strating from the market research, over

production strategy to the communication with

customers. Mass customization is a production strategy

focused on creation of products that are uniquely

customized to the customers. To produce personalized

products or services, and provide unique value to their

customers, companies increasingly involve customers in

product and service development – a process of co-

creation.

2. THEORETICAL BACKGROUND

This part of the paper will cover theoretical

fundamentals from the field of mass customization and

co-creation, social media and data mining in social

media.

2.1. Mass customization and co-creation

The market is constantly changing, the rules and

conditions of business also, competition becomes very

intense, and what customers want today are products and

services made exclusively according to their wishes and

requirements. So, the most important competitive

advantage for every business has to be the diversification

of products that adapt to specific customer needs.

Customers become more self-aware and more

demanding in their buying preferences and in the light of

growing trends towards sustainable consumption mass

customization becomes a strong drive for the

implementation of sustainable products and services [1].

Focusing on the customer, however, is both an

imperative and a potential curse and in order to meet all

the requirements of customers, many companies

implement different technologies and production

strategies. Some authors claim that mass customization

as a state-of-the-art production paradigm aims to produce

individualized, highly variant products and services with

nearly mass production costs [2]. On the other side,

customers and their needs grow increasingly diverse,

such an approach has become a surefire way to add

unnecessary cost and complexity to operations. Available

information technology and flexible work processes

MASS CUSTOMIZATION AND CO-

CREATION ON SOCIAL NETWORKS

Danijela Gračanin, Danijela Ćirić, Branislav Stevanov, Jelena Stanković, Jelena Ćurčić University of Novi Sad, Faculty of Technical Sciences, Novi Sad, Republic of Serbia

c o m m u n i t y o f e u r o p e

th8 International Conference on Mass Customization and Personalization – Community of Europe (MCP-CE 2018)

Digital Customer ExperienceSeptember 19-21, 2018, Novi Sad, Serbia

142

permit companies to customize goods or services for

individual customers in high volumes and at a relatively

low cost, but many managers have discovered that mass

customization, too, can produce unnecessary cost and

complexity [3]. Probably, they have not yet found the

appropriate kind of customization their customers would

value before they plunged ahead with this new strategy.

Mass customization cannot succeed without a marketing

and sales teams that understand the demand for

customized products. Companies must first identify

opportunities for customization that create value for the

customer and are supported by smooth, swift and

inexpensive transactions for both consumers and

producers and second achieve a manageable cost

structure and cost level for producer even as

manufacturing complexity increases [4]. Also, one

research found that work‐design practices that manage

both the technical and the social dimensions for

achieving organization success have significant impact

on a company's ability to achieve mass customization

[5].

But customers are ready to pay extra costs and

purchase more favorable products if they have a chance

to co-create new product together with producer [6].

Then, .customers create innovative products and realize

value by collaborating with manufacturers and other

consumers. Mass customization was enabled by several

important concepts and technologies, including product

family architecture, reconfigurable manufacturing

systems, and delaying differentiation and in the most

cases the role of the consumer is limited to choosing the

module combinations [7]. A company that has one or a

few customers can produce customization by

collaborating with each one to produce exactly what,

when, where and how an offering is delivered, but mass

market companies have to take a scalable approach to

involving customers in these processes [8]. The

traditional system of company‐centric value creation is

becoming obsolete, so interaction as a basis for

co‐creation is now a necessity and co‐creation experience

of the consumer becomes the very basis of value [9]. It

was also found that when customers are allowed to

participate and are provided with more choices, it leads

to a higher level of trust and any ignorance in this

process may bring in negative effect of relational value

on customer recommendation [10]. Social media can

make economic‐exchange relations more collaborative

and social, but interestingly may also turn relations

formerly based on social‐exchange into "money markets"

with strong competition among actors [11].

2.2. Social media

In recent years, mass media has changed and adopted

a new phenomenon called social media. The first part of

this terminology, social, refers to the need of people to

connect and communicate with other people. And the

second part of this term refers to the media that people

use to connect with other people. The rise of interactive

digital media has changed the model of communication

between companies and customers. Customers

increasingly use digital media not only to explore

products and services, but to interact with the companies

they buy from and also with other customers who can

have valuable and important insights into the product or

service. The most popular and most widely used

definition of social media is "group of Internet-based

applications that build on the ideological and

technological foundations of the Web 2.0 and that allow

the creation and exchange of user-generated content"

[12]. The main advantage of social media is the

possibility of greater interaction and individualization.

Social media humanize customer services, attract

customers to the company and make the information

more accessible. The availability of advanced analytics,

inexpensive data storage, advanced search capabilities

allows companies to offer non-generalized and truly

customized offers to their customers. Digital marketing

also helps in identifying trends and patterns of customer

behavior and companies can use to attract customers on

their websites. It is considered that one of the reasons

why user-generated media is so popular is the fact that

they are easy to use and controlled by users. Business

executives, consultants, and decision makers alike all

struggle with understanding and decrypting how to best

make use of the various social media applications that

are available in the marketplace [13]. The Internet has

extended consumers‟ options for gathering product

information from other consumers and provides the

opportunity for consumers to offer their own

consumption-related advice by engaging in electronic

word-of-mouth (eWOM) [14]. Programmability,

popularity, connectivity and datafication are the four

elements of social media and most important in

understanding how in a networked society social

interaction is mediated by an intricate dynamic of mass

media, social media platforms, and offline institutional

processes [15]. Social commerce is a new phenomenon

rooted in social media practice and further understanding

of social commerce phenomenon is essential for

companies to achieve their profitable marketing values in

today‟s digital business environment [16].

The most popular social networks that companies use

for B2C communication are: Facebook (social network),

Twitter (microblogging applications), YouTube (video

sharing tool), Pinterest and Instagram as photos sharing

tools. In this paper, special emphasis will be on Twitter.

Twitter is a social networking and microblogging

service, enabling registered users to read and post short

messages, so-called tweets. Twitter messages are limited

to 280 characters and users are also able to upload photos

or short videos. Tweets are posted to a publicly available

profile or can be sent as direct messages to other users.

Twitter is one of the most popular social networks

worldwide. Part of the appeal is the ability of users to

follow any other user with a public profile. In the second

quarter of 2018, the micro-blogging service averaged at

335 million monthly active users (Source: The Statistics

Portal - Statista). Twitter tracks phrases, words, and

hashtags that are most often mentioned and posts them

under the title of "trending topics" regularly [17]. The

most important elements on Twitter are [18]:

1. Hashtag - allows to explicitly mark the topic of a

tweet, start with character „#” and can be common word

or concatenation of several words. Tweet can contain any

number of hashtags and these hashtags can be placed at

any position in the text.

143

2. User References - users are identified by their

names prefixed with the character “@” Twitter users can

make references to other users.

2.3. Data mining in social media

The use of social media generates a large amount of

data and these data cover different topics such as

sociology, business, psychology, entertainment, politics,

news, events, etc. Such metadata includes: who is

speaking and sharing, where they are located, to whom

they are linked, how influential and active they are, what

their previous activity patterns look like and what this

suggests about their likely preferences and future

activities [19]. As a main type of “big data,” social media

is finding its many innovative uses, such as political

campaigns, job applications, business promotion and

networking, and customer services, and using and mining

social media is reshaping business models, accelerating

viral marketing, and enabling the rapid growth of various

grassroots communities [20]. Social media data are vast,

noisy, unstructured, and dynamic in nature. In order to

overcome these challenges, data mining techniques are

used by researchers to reveal insights into social media

data that would not be possible otherwise. This helps to

get a better understanding of the outlook of different

people regarding a certain subject, locate groups of

people among large communities of people, study

changes in group with reference to time, or even suggest

a certain product or task to acertain person by using data

mining in combination with social media [21]. Data

mining in social media can expand researchers'

capability of understanding new phenomena due to the

use of social media and improve business intelligence to

provide better services and develop innovative

opportunities. This is multidisciplinary area where

researchers of different backgrounds can make important

contributions.

3. RESEARCH METHODOLOGY AND RESULTS

Data is collected via registered Twitter application

which is used for authentication and communication with

the Twitter as social network. This enables the user to

gather the live tweets for certain hashtags, or to gather

the tweets published by registered user. All data is

collected and analyzed by using the Python language

scripts from [22]. The data collection script uses Twitter

Streaming API (Application Programming Interface).

Tweets were collected daily in the period of one week,

starting with 16.5.2018. and ending with 22.5.2018. Data

was collected by certain hashtag words and by a keyword

required by the data collection script. The collected data

is stored in a JSON file (JavaScript Object Notation).

Data analysis has been done by using scripts from [22]

and the results of data analysis are hashtag frequency,

mention frequency (user mentions), hashtag statistics and

time series chart.

Tweets are collected using the hashtags:

#MassCustomization,

#masscustom,

#3dprinting,

#AdditiveManufacturing,

#productconfigurator,

#cocreation,

#productcustomization.

Table 1. presents the date and the time period in

which the tweets are collected and the number of

collected tweets.

Table 1. Number of collected tweets

Date Time period Number of

collected tweets

Wednesday

16.5.2018. 14:30 - 23:26 2268

Thursday

17.5.2018. 7:40 - 16:10 2206

Friday

18.5.2018. 12:56 - 00:49 2553

Saturday

19.5.2018. 8:00 - 16:54 1785

Sunday

20.5.2018. 7:36 - 18:14 1621

Monday

21.5.2018.

10:15 - 20:35

with break

12:54 - 14:20

2411

Tuesday

22.5.2018. 5:46 - 15:45 2193

Figures 1-7 present time series for collected tweets for

seven dates respectively.

Fig. 1. Twitter time series for 16.5.2018.


144






Tweet hashtag frequencies for the seven dates are

presented in the Table 2.

Table 2. Tweet hashtag frequencies

Wednesday

16.5.2018.

3dprinting: 950

iot: 156

ai: 141

additivemanufacturing: 109

robotics: 99

drones: 92

blockchain: 91

emergingtechnologies: 85

future: 70

tech: 67

3dprinted: 64

innovation: 61

machinelearning: 60

cybersecurity: 59

logistics: 59

dataanalytics: 58

ar: 57

vr: 53

technology: 52

manufacturing: 52

Thursday

17.5.2018.

3dprinting: 1180

manufacturing: 284

industry40: 255

iot: 119

ai: 111

3dthursday: 91


blockchain: 57

cybersecurity: 54

technology: 51

3dprinted: 48

digitaltransformation: 46

robotics: 44

3dprint: 42

3dprinter: 39

it: 39

innovation: 39

bigdata: 37

Friday

18.5.2018.

3dprinting: 879

industry40: 154

manufacturing: 109

iot: 91

ai: 80

145


3dprinted: 71

smartcity: 58

bigdata: 57

socialmedia: 56

smarthome: 55

futureofwork: 55

digital: 54

technology: 53

cloud: 47

3dprinter: 38

innovation: 37

emergingtech: 36

climateaction: 36

Saturday

19.5.2018.

3dprinting: 462

industry40: 88

ai: 87, iot: 86

manufacturing: 52

bigdata: 50

3dprinted: 40

cloud: 38

technology: 35


blockchain: 33

tech: 2, robotics: 28

3dprint: 27

cybersecurity: 27


emergingtech: 25

Sunday

20.5.2018.

3dprinting: 639

ai: 138

industry40: 96

3dprinted: 88


robotics: 69

emergingtech: 64

healthcare: 63

wireless: 59

biotech: 59

iot: 50

disrupt: 49

manufacturing: 44

3dprint: 43

tech: 42

machinelearning: 40

Monday

21.5.2018.

3dprinting: 799

ico: 589

tokens: 580

3dprints: 579

manufacturing: 112

industry40: 89

3dprinted: 83

iot: 82, technologies: 73

ai: 66

smartcity: 47

blockchain: 41

drones: 41


3dprint: 34, scifi: 34

3dprinter: 33

toydesign: 33

Tuesday

22.5.2018.

3dprinting: 840

ico: 322, 3dprints: 312

tokens: 311

manufacturing: 114


industry40: 80

ai: 77, iot: 71

healthcare: 75

technologies: 67

aerospace: 63

drones: 47

3dprint: 46

3d: 45,

3dprinted: 39


infographic: 31

robotics: 31

The research is done in seven days including

working days and weekend, and has shown that people

definitely talk about Mass Customization on the Twitter.

But, unlike the previous similar research on the topic

connecting with industry 4.0 [23], the number of tweets

in a similar period of time is 4 times lower in Mass

Customization. This is expected because mass

customization is too narrow as a topic. Observing the

frequency of the tweets during the data collection

period, the highest number of tweets per hour is 17. On

weekend the number of tweets is lover by 30%

approximately. On working days the number of tweets

is more or less the similar. Areas in which the mass

customization topics are mentioned cover

manufacturing, healthcare, robotics, biotech and

aerospace. The most frequently mentioned words

related to this topic are 3D Printing, Additive

manufacturing, Industry 4.0 and Internet of Things. 3D

printing excels other hashtags by 5 to 10 times per

collection period. In the research a geolocation tweets

map was also generated for every day, but since very

small number of tweets included this data, the generated

maps were empty and this analysis is ommited.

4. CONCLUSION

Information about mass customization and co-

creation are present in industry and science, but valuable

data could also be found on social networks. The aim of

this paper was primarily to show whether the topic of

Mass Customization is popular on Twitter, how often

people talk about it and what topics are related. Given

the fact that the total number of monthly active Twitter

users is about 335 million, on the one side and

importance of social media in creating of customer

behavior on the other side, this can be used as a powerful

tool for promotion of mass customization concept and its

benefit. This is just first step in this ”reesearch journey”

through social media. Future research will oriented

toward detailed analyse of tweet content. Also, Facebook

will be included using the same methodology.

5. REFERENCES

[1] A. Hänsch, J. Mohr, I. Steinberg, S. Gomez and M.

Hora, “Opportunities and Challenges of Product-

Service Systems for Sustainable Mass Customization:

146

A Case Study on Televisions” in Customization 4.0.

Springer Proceedings in Business and Economics,

Springer, pp 265-284, 2018

[2] J. H. Gilmore and B. J. Pine, “The four faces of mass

customization”, Harvard Business Review, vol. 75,

no. 1, pp 91-101, Jan-Feb1997.

[3] J. Tiihonen and A. Felfernig, “An introduction to

personalization and mass customization”, Journal of

Intelligent Information Systems, vol. 49, no. 1, pp. 1-

7, August 2017

[4] A. Gandhi, C. Magar and R. Roberts, “How technology

can drive the next wave of mass customization: seven

technologies are making it easier to tailor products and

services to the wants of individual customers - and still

make it a profit”, McKinsey on Business Technology,

no. 32, winter 2013

[5] G. Liu, R.Shah and R. G. Schroeder, “Linking Work

Design to Mass Customization: A Sociotechnical

Systems Perspective”, Decision Sciences, vol. 37, no.

4, pp. 519-545, November 2006

[6] M. Park and J. Yoo, “Benefits of mass customized

products: moderating role of product involvement

and fashion innovativeness”, Heliyon, vol. 4, no. 2,

pp. 1-25, February 2018.

[7] S. Jack Hu, “Evolving Paradigms of Manufacturing:

From Mass Production to Mass Customization and

Personalization”, Procedia CIRP, vol. 7, pp. 3-8, 2013.

[8] J. Loef, B. Joseph Pine II and H. Robben, "Co-

creating customization: collaborating with customers

to deliver individualized value", Strategy &

Leadership, vol. 45, no. 3, pp.10-15, 2017

[9] C.K. Prahalad and V. Ramaswamy, "Co‐creating

unique value with customers", Strategy &

Leadership, vol. 32, no. 3, pp.4-9, 2004

[10] M. Fellesson and N. Salomonson, “The expected

retail customer: Value co-creator, co-producer or

disturbance?”, Journal of Retailing and Consumer

Services, vol. 30, pp. 204-211, May 2016

[11] F. T. Piller, A. Vossen and C. Ihl, “From Social

Media to Social Product Development: The Impact of

Social Media on Co-Creation of Innovation”, Die

Unternehmung, vol. 65, no. 1, pp. 1-22, 2012.

[12] A. M. Kaplan and M. Haenlein, “Users of the world,

unite! The challenges and opportunities of social

media”, Business Horizons, vol. 53, no. 1, pp. 59–68,

January–February 2010.

[13] A. M. Kaplan, “Social Media, the Digital

Revolution, and the Business of Media”, International

Journal on Media Management, vol.17, no. 4, pp.

197-199, December 2015.

[14] T. Hennig – Thurau, K.P. Gwinner, G. Walsh and

D.D. Gremler, “Electronic word-of-mouth via

consumer-opinion platforms: what motivates

consumers to articulate themselves on the internet?”,

Journal of Interactive Marketing, vol. 18, no. 1, pp.

38-52, 2004.

[15] J. van Dijck and T. Poell, “Understanding Social

Media Logic”, Media and Communication, vol. 1, no.

1, pp. 2-14, August 2013

[16] X.Lin, Y. Li and X. Wang, “Social commerce

research: Definition, research themes and the trends”,

International Journal of Information Management, vol.

37, no. 3, pp. 190-201, 2017.

[17] H. Kwak, C. Lee, H. Park and S. Moon, “What is

Twitter, a social network or a news media?”, in

Proceedings of the 19th international conference on

World wide web (WWW '10), pp. 591-600, 2010

[18] J. Atserias, and J. Codina, “What is the text of a

Tweet?”, in Proceedings on the International

Conference on Language Resources and Evaluation,

pp. 29-33, 2012

[19] H. Kennedy and G. Moss, “Known or knowing

publics? Social media data mining and the question

of public agency”, Big Data & Society, pp. 1-11,

October 2015.

[20] P. Gundecha and H, Liu, “Mining Social Media: A

Brief Introduction”, INFORMS TutORials in

Operations Research, pp. 1-17, October 2014.

[21] G. Barbier and H. Liu H, “Data Mining in Social

Media”, Chapter in Social Network Data Analytics,

pp. 327-352, 2011.

[22] M. Bonzanini, “Mastering social media mining with

Python”, Packt Publishing Ltd, 2016.

[23] B. Stevanov, D. Gracanin, N. Suzic, Z. Tesic,

“Visibility of Industry 4.0 on social networks”, in

Proceedings on XVII International Scientific

Conference on Industrial Systems, October 2017.

CORRESPONDENCE

Dr Danijela Gračanin, Assist. Prof.

University of Novi Sad

Faculty of Technical Sciences,

Trg Dositeja Obradovića 6

21000 Novi Sad, Serbia

[email protected]

Dr Branislav Stevanov, Assist. Prof.





[email protected]

Danijela Ćirić, Teach. Assistant





[email protected]

Jelena Stanković, Teach. Assistant





[email protected]

Jelena Ćurčić, Teach. Associate





[email protected]

147

mailto:[email protected]





Documents

MASS CUSTOMIZATION AND CO- CREATION ON SOCIAL …